No, what's required is that the AI develop mappings into it's model of
the universe (derived from its own sensors) from the artificially
constructed model. This is the way one learns mathematical physics, or
reading music (and, I presume, reading in general, but I don't remember
that). It's different from the pure kinesthetic learning involved in
"how to hit a ball with a stick", but it's still learning, and still a
part of what it means to be a GAI.
Günther Greindl wrote:
The problem with all traditional knowledge bases (CYC too) it is still
all meaningless symbols for the processing computer program, processed
according to relational rules in the KB, which are all entered by
_human beings_.
An AI would need to develop it's own KB, like a child - we all have
our own little KB's in our brains, each developed individually be
their education and experiences.
The KB which the AI would learn would not make sense to us, of course;
as little as the neural connections in a human brain make sense to us
(in the sense of "concepts").
Regards,
Günther
Benjamin Goertzel wrote:
Matt,
I agree w/ your question...
I actually think KB's can be useful in principle, but I think they
need to be developed
in a pragmatic way, i.e. where each item of knowledge added can be
validated via
how useful it is for helping a functional intelligent agent to achieve
some interesting
goals...
ben g
What would you do with the knowledge base after you build it? I
know this
sounds like a dumb question, but Cyc has built a huge base of common
sense
knowledge in a structured format, but it isn't useful for anything.
Of course
that is not the result they anticipated. How will you avoid the
same type of
(very expensive) failure? What type of knowledge will it contain?
-- Matt Mahoney, [EMAIL PROTECTED]
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